Skin color detection for face localization in human-machine communications

This paper presents the proposed user interface design for computers whereby users can navigate in a 3D graphics scene and change camera viewpoint via head movement. This human-machine communication relies very much on the performance of its face localization module, which must determine head pose and track head movement. We have employed the skin color detection approach to face localization. The approach is studied and presented. The experimental results show that our chosen methodology is very effective. Furthermore, we demonstrate that skin color detection approach can cope with the variations of skin color and lighting condition

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio